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—Hyperspectral images consist of large number of bands which require sophisticated analysis to extract. One approach to reduce computational cost, information representation, and accelerate knowledge discovery is to eliminate bands that do not add value to the classification and analysis method which is being applied. In particular, algorithms that perform(More)
We present performance results of a new method for computing eigenvectors of a real symmetric tridiagonal matrix. The method is a variation of inverse iteration and can in most cases substantially reduce the time required to produce orthogonal eigenvectors. Our implementation of this algorithm has been quite eeective in solving \degenerate" eigenproblems in(More)
With the growing popularity of parallel computation, researchers are looking for various means to reduce the problem solving time by performing the computations in parallel. While, interested in parallel computation they do not want to deal with the parallel programming complexities. In this paper, through RScaLAPACK we demonstrate a means that enables the(More)
For a finite but arbitrary precision, we construct efficient low separation rank representations for the Poisson kernel and for the projector on the divergence free functions in the dimension d = 3. Our construction requires computing only one-dimensional inte-grals. We use scaling functions of multiwavelet bases, thus making these representations available(More)
We develop a multiresolution representation of a class of integral operators satisfying boundary conditions on simple domains in order to construct fast algorithms for their application. We also elucidate some delicate theoretical issues related to the construction of periodic Green's functions for Poisson's equation. By applying the method of images to the(More)
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